Neurology

Intraoperative Navigation and Robotics in Pediatric Spinal Deformity.

Current technologies for image guidance navigation and robotic assistance with spinal surgery are improving rapidly with several systems commercially available. Newer machine vision technology has several potential advantages. Limited studies have shown similar outcomes to traditional navigation platforms with decreased intraoperative radiation and time required for registration. However, there ar...

An Unsupervised Learning-Based Regional Deformable Model for Automated Multi-Organ Contour Propagation.

The aim of this study is to evaluate a regional deformable model based on a deep unsupervised learning model for automatic contour propagation in breast cone-beam computed tomography-guided adaptive radiation therapy. A deep unsupervised learning model was introduced to map breast's tumor bed, clinical target volume, heart, left lung, right lung, and spinal cord from planning computed tomography t...

The effect of robot-assisted gait training frequency on walking, functional recovery, and quality of life in patients with stroke.

AIM: This study aims to investigate the effects of robot-assisted gait training (RAGT) frequency on walking, functional recovery, QoL and mood.

The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke.

BACKGROUND: Robots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical or...

Can MRI Be Used as a Sensor to Record Neural Activity?

Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review...

Application of deep learning algorithms in automatic sonographic localization and segmentation of the median nerve: A systematic review and meta-analysis.

OBJECTIVE: High-resolution ultrasound is an emerging tool for diagnosing carpal tunnel syndrome caused by the compression of the median nerve at the w...

Cost-effectiveness analysis of overground robotic training versus conventional locomotor training in people with spinal cord injury.

BACKGROUND: Few, if any estimates of cost-effectiveness for locomotor training strategies following spinal cord injury (SCI) are available. The purpos...

An Efficient Machine Learning-Based Emotional Valence Recognition Approach Towards Wearable EEG.

Emotion artificial intelligence (AI) is being increasingly adopted in several industries such as healthcare and education. Facial expressions and tone...

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strate...

State-of-the-art Applications of Patient-Reported Outcome Measures in Spinal Care.

Patient-reported outcome measures (PROMs) assign objective measures to patient's subjective experiences of health, pain, disability, function, and qua...

Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat).

Diffusion MRI is a useful neuroimaging tool for non-invasive mapping of human brain microstructure and structural connections. The analysis of diffusi...

Pleasant Stroke Touch on Human Back by a Human and a Robot.

Pleasant touching is an important aspect of social interactions that is widely used as a caregiving technique. To address the problems resulting from ...

Precise Discrimination for Multiple Etiologies of Dementia Cases Based on Deep Learning with Electroencephalography.

INTRODUCTION: It is critical to develop accurate and universally available biomarkers for dementia diseases to appropriately deal with the dementia pr...

Extracting a Novel Emotional EEG Topographic Map Based on a Stacked Autoencoder Network.

Emotion recognition based on brain signals has increasingly become attractive to evaluate human's internal emotional states. Conventional emotion reco...

Original research: utilization of a convolutional neural network for automated detection of lytic spinal lesions on body CTs.

OBJECTIVE: To develop, train, and test a convolutional neural network (CNN) for detection of spinal lytic lesions in chest, abdomen, and pelvis CT sca...

Toward a generalizable deep CNN for neural drive estimation across muscles and participants.

High-density electromyography (HD-EMG) decomposition algorithms are used to identify individual motor unit (MU) spike trains, which collectively const...

The identification of interacting brain networks during robot-assisted training with multimodal stimulation.

Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for a...

Neurodegenerative disease of the brain: a survey of interdisciplinary approaches.

Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective t...

Deep learning-based personalised outcome prediction after acute ischaemic stroke.

BACKGROUND: Whether deep learning models using clinical data and brain imaging can predict the long-term risk of major adverse cerebro/cardiovascular ...

[Artificial intelligence and ethics in healthcare-balancing act or symbiosis?].

Artificial intelligence (AI) is becoming increasingly important in healthcare. This development triggers serious concerns that can be summarized by si...